The invention relates to video processing, and more specifically, to methods and systems for enhancing the color-saturation contrast of a video signal.
A video signal carries a sequence of video images, each of which is composed of pixels. Each pixel has a value representing the property of the video image at a particular location. Pixel values of the video image must conform to a specified range, for example, a fixed number of bits representing each pixel defines the number of allowable pixel values for output or display, or an output device only supports a certain range of pixel values. The majority of video images output to or displayed on an output device do not make effective use of the full range of pixel values available on the output device. The pixel values of the video image might concentrate in a small portion of the available range, causing the visual appearance to be relatively dull. A contrast enhancer may improve the appearance of the video images by expanding or remapping the pixel values to full scale.
A conventional contrast enhancer employs a histogram equalization method by adjusting luminance values. The pixel values of the video images are altered by histogram equalization to distribute the luminance values as uniformly as possible. The equalization method comprises calculating a normalized cumulative histogram of the luminance values, and remapping the luminance values according to the normalized cumulative histogram.
U.S. Pat. No. 5,822,453 teaches a method for estimating the scene contrast by sampling high contrast pixels and calculating the standard deviation of their log-exposure distribution as a measure of the scene contrast. The input image contrast is adjusted based on the comparison result of the calculated standard deviation and mean contrast of the precompiled population scene contrasts. The contrast is adjusted through a histogram modification process, where the original histogram is mapped through a tone transformation curve into the target histogram. The process comprises forming an intensity histogram that eliminates pixels corresponding to uniform areas or textured portion of the image, and constructing the tone transformation curve by convolving the intensity histogram with a Gaussian distribution.
Video signals carries a luminance signal representing the lightness variation and a chrominance signal representing chromatic variation in the image. Contrast enhancers may improve the image appearance by adjusting either the luminance signal or chrominance signal, or both. A contrast enhancer disclosed in U.S. Pat. No. 5,808,697 tunes the luminance signal by dividing each image into block-shaped areas and calculating a mean luminance level for each area. A selection signal is adjusted in small steps according to the mean luminance levels. The luminance level of the video signal is mapped according to a mapping function selected by the selection signal. The disclosed contrast enhancer also tunes the chrominance signal using the histogram equalization method.